Humanoid robots are important research targets because they imitate humans and can be easily imagined as an alternative to the labor force. Conventional humanoid robots are mainly controlled by numerical calculations using CPUs. However, realizing real-time motion control requires a high-performance CPU with high power consumption due to the need for high-speed processing of a huge amount of numerical calculations. This leads to the problem of overloading the on-board battery. In response to this problem, there is the concept of imitating human motion control, since humans are active with energy as low as 100[W] in terms of electricity. Based on this concept, our study has focused on artificial neural networks composed of analog electronic circuits to mimic the central pattern generator (CPG) of the neural network involved in human gait control without using numerical calculations. The objective of this paper is to develop a hardware CPG model for controlling both legs of a musculoskeletal humanoid robot, engineering a mimicry of human muscles and skeleton. Circuit simulations of the constructed hardware CPG model were performed, and it was confirmed that a gait pattern was generated for both legs.

This paper discusses a new kinematics of two-wheeled mobile robot. Most kinematics of mobile robots are related to velocity, but this paper discusses position-based kinematics. Regarding wheeled mobile robots, position-based kinematics is an ill-posed problem because the solution is not uniquely determined. However, this study reveals a new regularization method for this ill-posed problem. This regularization method imposes a certain constraint on the wheel motion, unlike the standard regularization theory attributable mainly to Tikhonov regularization. This paper derives an analytical solution of position-based forward kinematics subject to the constraint of wheel motion. This paper also shows that the analytical solution is consistent with the integrability of non-holonomic constraints and results of experimental verification.

The burden of childcare for the terrible twos is enormous and has become a serious problem. Therefore, a balance between reducing the burden of childcare and providing detailed supervision of toddlers is required. A plushie device was developed that can safely measure the toddler's behaviors for a long time, including externalizing behaviors such as throwing and hitting. This study aims to elucidate the characteristics of sensor responses from data that reflect the toddler's state and behavior, and to demonstrate an analysis method that makes it possible to understand the relationship with the toddler's behavior. Using the developed plushie, we experimented to measure the behavior of the terrible twos in the home. The acquired data is visualized by creating a histogram for each sensor and compared with the results from the guardian questionnaire. We suggest the acceleration sensor reacts to any movement, such as car travel, whereas the bending sensor reacts to the intentional contact of a toddler, such as playing. Both the frequency and intensity of contact decreases when the toddler is unhealthy or in a bad mood. Consequently, car travel actions are successfully labeled using machine learning while showing the usefulness of appropriately selecting sensors and statistics for analysis.

This paper proposes a vertical locomotion mechanism with wheels for elevator installation work that grasps a vertically hung piano wire and runs on it. To meet the functional requirements, a friction-driven method using a self-servo effect was applied to generate the sufficient amount of grasping force. The shape and material of the wheel that can generate sufficient grasping force without causing breakage of both of the piano wire and the wheels are found, and its grasping performance is investigated through experiments. Based on these results, a prototype that can grasp the piano wire and run on it is designed and built, and succeeded in stable grasping and lifting and lowering operation through experiments. Furthermore, an improved prototype having the measuring wheel to compensate wheel slippage and the reaction wheel to suppress machine rotation is built and succeeded in reciprocating lifting and lowering experiment. Through, the effectiveness of the proposed vertical locomotion mechanism is confirmed.

A flexible and stable underwater wireless communication method is needed to realize cable-free underwater robots. However, commonly used acoustic communication is susceptible to multipath and difficult to communicate in polar and shallow water regions. In this study, we developed a system that enables a remote operator to remotely control a robot deployed underwater by combining visible light wireless communication and satellite communication. As a result of a demonstration experiment, an underwater robot in Hokkaido was successfully remote-controlled from Tokyo.

We have developed an ankle joint of the humanoid robot that can measure the joint torque. The system measures the strain of the CFRP leaf spring and calculates the torque by it. Also, the joint includes a variable joint quasi-stiffness mechanism to imitate the elasticity and the torque of human during running. Experiments confirmed that it is possible to measure the joint exerted torque.

Multipoint soil condition measurements are expected to be utilized for localized control of fertilization to enhance agricultural productivity. However, existing soil measurement methods are time-consuming and labor-intensive. To deal with this challenge, this study assumes the scenario of a crop-free field and allows for the measurement position error. The robot could be downsized and its movement speed enhanced. The proposed robot measures soil conditions of 560[m²] field in 22[min] 30[sec] — a 16-time improvement over our previous research. Moreover, the robot is lighter by 50% and occupies only 1/6th of the size compared to the previous study.

Currently, stem removal of cherry tomatoes for food processing is manually performed and time-consuming. Toward automation of the operation, in this paper, we propose a stem removal method for cherry tomatoes that can avoid their dehiscence by using an iris mechanism. We find an appropriate pulling force, the effectiveness of rotating a stem, and the importance of aligning the axes of the stem and the rotation through a prior experiment. Based on the findings, we develop an iris mechanism for grasping a stem and experimentally verify the feasibility of stem removal for cherry tomatoes without their dehiscence.